LEADER 04119nam 2200553 450 001 9910822444703321 005 20170918154647.0 010 $a1-78439-750-4 035 $a(CKB)3710000000471228 035 $a(EBL)4191251 035 $a(SSID)ssj0001611411 035 $a(PQKBManifestationID)16323161 035 $a(PQKBTitleCode)TC0001611411 035 $a(PQKBWorkID)14900501 035 $a(PQKB)11482192 035 $a(MiAaPQ)EBC4191251 035 $a(CaSebORM)9781784397180 035 $a(PPN)22804295X 035 $a(EXLCZ)993710000000471228 100 $a20160105d2015 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aClojure for data science $estatistics, big data, and machine learning for Clojure programmers /$fHenry Garner 205 $a1st edition 210 1$aBirmingham :$cPackt Publishing,$d2015. 215 $a1 online resource (608 p.) 225 1 $aCommunity experience distilled 300 $aIncludes index. 311 $a1-78439-718-0 320 $aIncludes bibliographical references and index. 330 $aStatistics, big data, and machine learning for Clojure programmers About This Book Write code using Clojure to harness the power of your data Discover the libraries and frameworks that will help you succeed A practical guide to understanding how the Clojure programming language can be used to derive insights from data Who This Book Is For This book is aimed at developers who are already productive in Clojure but who are overwhelmed by the breadth and depth of understanding required to be effective in the field of data science. Whether you're tasked with delivering a specific analytics project or simply suspect that you could be deriving more value from your data, this book will inspire you with the opportunities?and inform you of the risks?that exist in data of all shapes and sizes. What You Will Learn Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with confidence Implement the core machine learning techniques of regression, classification, clustering and recommendation Understand the importance of the value of simple statistics and distributions in exploratory data analysis Scale algorithms to web-sized datasets efficiently using distributed programming models on Hadoop and Spark Apply suitable analytic approaches for text, graph, and time series data Interpret the terminology that you will encounter in technical papers Import libraries from other JVM languages such as Java and Scala Communicate your findings clearly and convincingly to nontechnical colleagues In Detail The term ?data science? has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist's diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you'll see how to make use of Clojure's Java interoperability capabilities to access libraries such as ... 410 0$aCommunity experience distilled. 606 $aClojure (Computer program language) 606 $aBig data 606 $aMachine learning 615 0$aClojure (Computer program language) 615 0$aBig data. 615 0$aMachine learning. 700 $aGarner$b Henry$01680810 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910822444703321 996 $aClojure for data science$94049786 997 $aUNINA